Dr. Fabian Scheipl, Dr. Sabine Hoffmann, Daniel Schlichting
2024-02-13
1. Overview & Terminology
2. Data Analysis
3. Summary
1. Overview & Terminology
2. Data Analysis
3. Summary
VR-Training: Adapting Virtual Reality Training Applications by Dynamically Adjusting Visual Aspects
Motivation:
- Static training doesn’t fit everyone: Too easy → boredom, Too hard → anxiety
- Adaptive VR training balances difficulty to improve outcomes.
Scenario:
- Users move and place parcels in a VR warehouse using controllers.
- Visual cues: dynamic lighting and color guidance.
Adaptive Features:
- Tracks user behavior (head movement) and performance (time, errors).
- Adjusts lighting, object colors, etc., after each training round.
1. Overview & Terminology
2. Data Analysis
3. Summary
1. Are there differences between the 2 data cohorts, Linne and Dame?
→ Despite demographic and protocol differences, the two cohorts are similar enough in key characteristics to allow meaningful comparison.
2. How are the stress indicators and the physiological measurements related?
3. Does this correlation change over the rounds?
4. Are there subgroups within the test subjects that stand out from the rest?
1. Overview & Terminology
2. Data Analysis
- Cohorts comparison: Similarities and Differences
- Relationship between Stress indicators and Physiological Measurements
- Relationship over the rounds
- Subgroups and Outliers
3. Summary
⇒ Values of the correlation vary from -0.15 to 0.1, indicating very weak relationship between the stress indicators and the physiological measurements
3. Does this correlation change over the rounds?
4. Are there subgroups within the test subjects that stand out from the rest?
1. Overview & Terminology
2. Data Analysis
- Cohorts comparison: Similarities and Differences
- Relationship between Stress indicators and Physiological Measurements
- Relationship over the rounds
- Subgroups and Outliers
3. Summary
1. Are there differences between the 2 data cohorts, Linne and Dame?
2. How are the stress indicators and the physiological measurements related?
→ The correlation between physiological measurements and stress indicators shows minimal changes across the rounds, correlation values mostly falling within the range of -0.2 to 0.2 and no consistent trend observed.
4. Are there subgroups within the test subjects that stand out from the rest?
1. Overview & Terminology
2. Data Analysis
- Cohorts comparison: Similarities and Differences
- Relationship between Stress indicators and Physiological Measurements
- Relationship over the rounds
- Subgroups and Outliers
3. Summary
The plot shows that as cognitive load increases, RMSSD decreases, with high HRV defined as RMSSD values above the 0.9 quantile, indicating lower autonomic flexibility under stress.
1. Are there differences between the 2 data cohorts, Linne and Dame?
2. How are the stress indicators and the physiological measurements related?
3. Does this correlation change over the rounds?
→ something something conclusion
1. Overview & Terminology
2. Data Analysis
3. Summary
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